KF7009 - Decision Support Systems

APPLY NOW BOOK AN OPEN DAY Add to My Courses Register your interest / Course PDF

What will I learn on this module?

This module provides you with the opportunity to learn about state-of-the-art technologies and research work in decision support methods, tools and techniques. You will learn about the fundamentals of tackling decisions of increasing difficulty and about computerized methods for knowledge extraction, knowledge fusion and management to support decision making. These will include machine learning, artificial intelligence, data warehousing and data mining approaches with examples of various application areas, including economic and industrial engineering ones. You will implement computerised decision support systems for specific real-life problems.

In particular, the module syllabus will cover the following topics:

• Decision-Making Systems and Models
• Data Warehousing, Data Mining
• Modelling and Analysis, Data Visualization
• Agent based modelling and simulation
• Game theory
• Multiple objective optimizations
• Genetic Algorithms
• Subgroup discovery
• The professional, ethical, legal, social issues, including security/data protection and implications of the development and use of decision support systems

Due to the research-based nature of the module, you will employ key research skills (e.g. using literature, using citation, critical analysis, evaluation etc.) throughout the module.

How will I learn on this module?

Lectures will introduce you to relevant theories and state-of-the-art decision-making system techniques and research work by well-known researchers. During lectures, you will be encouraged to be active participants in your learning, including through lecture based discussion.

Practical exercises will be provided in workshops to give you opportunities to practise and explore the techniques covered in the lectures with support from module staff. The practical exercises are designed to gradually equip you with the ability to design and develop decision support systems on your own. Additionally, during lectures and practical exercises you will also be guided on how to carry out relevant research. Inquiry-based learning is used throughout the module.

Outside of class contact time, you are expected to read research papers as guided independent learning. Guidance on accessing online or library resources will be given by the module team.

All module material will be available on the eLearning Portal (ELP) so that you can access information when you need to and we operate an open door policy to help support your learning. The university library offers support for all students through its catalogue and an Ask4Help Online service.

How will I be supported academically on this module?

The module team will guide and support you in the lecture and workshop practical sessions, including providing you with feedback on your work. During the lectures, you will be required to conduct interactive activities based on the lecturers’ guidance. The module team will prepare diverse examples of real-life applications to support you in learning complex decision support techniques. The module team will work closely with you in the practical sessions to conduct discussions and provide further detailed guidance on the subjects covered.

You can also request appointments with the module teaching team outside of scheduled class time to ask questions and seek advice.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

What will I be expected to achieve?

Knowledge & Understanding:
1. Apply in-depth knowledge and demonstrate critical understanding of decision support techniques

Intellectual / Professional skills & abilities:
2. Critically appraise decision support methods and tools, such as those for machine learning, data warehouse and data mining applications and intelligent processes
3. Working as a member of a team analyse a decision support problem and design, implement and test an appropriately advanced decision support system solution
4. Critically evaluate the effectiveness of the implemented decision support systems, considering professional, ethical, legal, security and social issues

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
5. Demonstrate research and enquiry in the construction of reports and presentation of a problem solution.

How will I be assessed?

Summative assessment
The module will be assessed by one individual assignment (worth 50% of the marks available) and a group project assignment (worth 50% of the marks available).

1. For the individual assignment you will critically review an academic paper from a list provided and will present your findings in a report and a presentation. This assignment will assess MLOs 1, 2, and 5.

2. In the group project you will work in a team to analyse a decision support problem and design, implement, test and critically evaluate a decision support system solution. Your team will document the solution, critically evaluate it and will also give a presentation on it. The group project will assess MLOs 1, 3, 4 and 5.

You will be provided with written, electronic, feedback for both of the summative assignments.

Formative assessment and feedback
The exercises in the lectures and practical sessions provide opportunities for formative assessment, helping you and your tutors to assess your progress. You will receive guidance and ongoing feedback on your work and progress verbally.

You will also have the opportunity to discuss your progress and the needs of the summative assessment informally in the practical class sessions.

Pre-requisite(s)

None

Co-requisite(s)

None

Module abstract

This module provides you with the opportunity to learn about state-of-the-art technologies and research work in decision support methods, tools and techniques. You will learn about tackling decisions of increasing difficulty and about computerized methods for knowledge extraction, knowledge fusion and management to support decision making. These will include machine learning, artificial intelligence, data warehousing and data mining approaches with examples of various application areas, including economic and industrial engineering ones. You will implement computerised decision support systems for specific real-life problems.

What will I learn on this module?

This module provides you with the opportunity to learn about state-of-the-art technologies and research work in decision support methods, tools and techniques. You will learn about the fundamentals of tackling decisions of increasing difficulty and about computerized methods for knowledge extraction, knowledge fusion and management to support decision making. These will include machine learning, artificial intelligence, data warehousing and data mining approaches with examples of various application areas, including economic and industrial engineering ones. You will implement computerised decision support systems for specific real-life problems.

In particular, the module syllabus will cover the following topics:

• Decision-Making Systems and Models
• Data Warehousing, Data Mining
• Modelling and Analysis, Data Visualization
• Agent based modelling and simulation
• Game theory
• Multiple objective optimizations
• Genetic Algorithms
• Subgroup discovery
• The professional, ethical, legal, social issues, including security/data protection and implications of the development and use of decision support systems

Due to the research-based nature of the module, you will employ key research skills (e.g. using literature, using citation, critical analysis, evaluation etc.) throughout the module.

Course info

UCAS Code G3F4

Credits 20

Level of Study Undergraduate

Mode of Study 4 years full-time or 5 years with a placement (sandwich)/study abroad

Department Computer and Information Sciences

Location City Campus, Northumbria University

City Newcastle

Start September 2019 or September 2020

Current, Relevant and Inspiring

We continuously review and improve course content in consultation with our students and employers. To make sure we can inform you of any changes to your course register for updates on the course page.

Your Learning Experience find out about our distinctive approach at 
www.northumbria.ac.uk/exp

Admissions Terms and Conditions - northumbria.ac.uk/terms
Fees and Funding - northumbria.ac.uk/fees
Admissions Policy - northumbria.ac.uk/adpolicy
Admissions Complaints Policy - northumbria.ac.uk/complaints